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Registers-Optimized neuro-Chip
Knowledge Emulation Technology (ROCKET™) is a software
simulator of a neural chip based on RBF (Radial Basis Function) architecture
and RCE (Restricted Coulomb Energy) learning algorithm. Unlike a software
"emulator" which can simply reproduce the functionality at the API
level, the software "simulator" reproduces all the registers of the
chip and performs bitwise operations on the registers in an extremely
efficient way. The simulator was written in C language using all the
potentialities that the language offers (inside our safety critical subset)
to speed up execution on Von Neumann machines. The simulation uses a
proprietary algorithm that speeds up the "broadcasting" operation
on a Von Neumann machine. This simulator cannot parallelize operations on
vector prototypes as the chip does: the hardware chip is based on a scalable
SIMD (Single Instruction Multiple Data) architecture. This simulator can be
considered the most efficient software implementation of an RBF-like neural
network architecture with RCE learning algorithm (classifier). The ROCKET™
simulator has been updated to be compliant with all the evolutions of the
chip from ZISC36® to ZISC78® to NM500® and ANM5500®. In the software simulation the number of
neurons is unlimited for all the versions. This neuro-Chip software
simulation has been successfully applied in the biomedical sector within an ECG
recognizer and in robotics within an anomaly detector for prognostic
maintenance. |
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©2024_Luca_Marchese_All_Rights_Reserved Aerospace_&_Defence_Machine_Learning_Company VAT:_IT0267070992 NATO_CAGE_CODE:_AK845 Email:_luca.marchese@synaptics.org |
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